Spatial variability of pores in oxidic latosol under a conservation management system with different gypsium doses
Bibliographic record
Abstract
Soil structure is modify when subjected to the agricultural process, i.e., a new spatial organization of the pores system is formed, with relation to the physical quality of it. Thus the aim of this work was to visualize and quantify, through X-ray CT scan, the pores distribution in an oxidic Latosol submitted to a conservation management system with different gypsum doses. Three random trenches were dug lengthwise along the plant row in a very clayey gibbsitic dystrophic Red Latosol, subjected to the following gypsum levels: G0: absence of gypsum; G7: 7 Mg ha-1 and G28: 28 Mg ha-1 of additional gypsum, applied to the surface of the plant row. Undisturbed soil samples were collected in plexiglass tubes at depths of 0.20-0.34, 0.80-0.94 and 1.50-1.64 m after six years of coffee cultivation for quantification of 3D pores obtained by X-ray CT scan. The spatial variability of the soil structure was evaluated by semivariograms generated by 3D images in grayscale. Distribution of the detectable pore diameter was conducted by data mining. Statistical analyzes employed packages 'geoR' to semivariogram and 'randomForest' for data mining in R language. A greater spatial continuity of the pores occurred in the G7 at the three depths. The combined effects of the management system promoted a greater spatial variability of the soil structure in the G28 treatment. Based on geostatistical analyses, it can be infer that the adoption of the system under study promoted changes in the pore network in all directions (X, Y and Z), however with better pores continuity in the vertical direction(Z).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".